Zhao T, Liu H, Bulloch G, Jiang Z, Cao Z, Wu Z. The influence of the COVID-19 pandemic on identifying HIV/AIDS cases in China: an interrupted time series study.
THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023;
36:100755. [PMID:
37360868 PMCID:
PMC10072954 DOI:
10.1016/j.lanwpc.2023.100755]
[Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/23/2023] [Accepted: 03/16/2023] [Indexed: 04/08/2023]
Abstract
Background
The COVID-19 pandemic has caused significant global public health challenges, and impacted HIV testing and reporting worldwide. We aimed to estimate the impact of COVID-19 polices on identifying HIV/AIDS cases in China from 2020 to 2022.
Methods
We used an interrupted time series (ITS) design and seasonal autoregressive integrated moving average intervention (SARIMA Intervention) model. Monthly reported data on HIV/AIDS cases were extracted from the National Bureau of Disease Control and Prevention of China from January 2004 to August 2022. Data on Stringency Index (SI) and Economic Support Index (ESI) from January 22, 2020 to August 31, 2022 were extracted from the Oxford COVID-19 Government Response Tracker (OxCGRT). Using these, a SARIMA-Intervention model was constructed to evaluate the association between COVID-19 polices and monthly reported HIV/AIDS case numbers from January 2004 to August 2022 using auto.arima () function from R. The absolute percentage errors (APEs) compared the expected numbers generated by the SARIMA-Intervention model with actual numbers of HIV/AIDS, and was the primary outcome of this study. A second counterfactual model estimated HIV/AIDS case numbers if COVID-19 hadn't occurred in December 2019, and the mean difference between actual and predicted numbers were calculated. All statistical analyses were performed in R software (version 4.2.1) and EmpowerStats 2.0 and a P < 0.05 was considered statistically significant.
Findings
The SARIMA-Intervention model indicated HIV/AIDS monthly reported cases were inversely and significantly correlated with stricter lockdown and COVID-19 related polices (Coefficient for SI = -231.24, 95% CI: -383.17, -79.32) but not with economic support polices (Coefficient for ESI = 124.27, 95% CI: -309.84, 558.38). APEs of the SARIMA-Intervention model for prediction of HIV/AIDS cases from January 2022 through August 2022, were -2.99, 5.08, -13.64, -34.04, -2.76, -1.52, -1.37 and -2.47 respectively, indicating good accuracy and underreporting of cases during COVID-19. The counterfactual model estimates between January 2020 and August 2022 an additional 1314 HIV/AIDS cases should have been established monthly if COVID-19 hadn't occurred.
Interpretation
The COVID-19 pandemic influenced the allocation and acquisition of medical resources which impacted accurate monthly reporting of HIV in China. Interventions that promote continuous HIV testing and ensure the adequate provision of HIV services including remote delivery of HIV testing services (HIV self-testing) and online sexual counseling services are necessary during pandemics in future.
Funding
Ministry of Science and Technology of the People's Republic of China (The grant number: 2020YFC0846300) and Fogarty International Center, National Institutes of Health, USA (The grant number: G11TW010941).
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